Pulmonary diseases rank third among the leading causes of death in the United States. The availability of high resolution MDCT makes it possible to image in-vivo lung structures in previously unattainable details, thus stimulating great interest of using imaging to phenotype lung abnormalities for better understanding of lung anatomy and its correlation to lung function. This may lead to earlier detection and diagnosis as well as possibly to more efficacious individualized patient management. There are indications that fissures integrity and configuration may be correlated with lung function and may play a role in the susceptibility of individuals to the development of specific lung diseases such as COPD (Chronic Obstructive Pulmonary Disease) and ILD (Interstitial Lung Disease). Fissure integrity may also be a primary factor in determining progression of diseases such as pneumonia. However, subjective assessments of fissures completeness and configuration as well as surrounding tissues are typically done subjectively by radiologists and pulmonologists and these assessments are both time consuming and error prone. To take advantages of available advanced CT imaging techniques and to provide a non-invasive way for assessing these relationships, we propose to develop automated computerized schemes to visualize and quantitatively measure and classify pulmonary fissures structure and completeness and then assess correlations, if any, between established lung function measures and differences in lung structures. To achieve these objectives, we will (1) assemble a large and diverse CT database of over 1000 lung CT examinations that cover a wide range of depicted lung diseases, (2) optimize a previously developed prototype computerized scheme for lung fissure detection and lobe segmentation and test its generalizeability, (3) develop an automated quantitative computerized tool for computing a summary index for fissure configuration and fissure incompleteness, (4) evaluate our computerized schemes by comparing it with the subjective results of three experienced radiologists, and (5) assess the correlation, if any, between lung anatomy and lung function using statistical analyses. The unique advantages of this project include but are not limited to: (1) pulmonary fissure/lobe analysis is performed, analyzed and visualized in three-dimensional geometric space using computational geometry analysis and as a result have minimum dependence on anatomical knowledge of lung structure, and (2) lung functions may be studied non-invasively by analyzing pulmonary structures reconstructed from high resolution CT images on either a lobe-by-lobe or a whole lung basis. We are encouraged by the success of our preliminary studies that supports the feasibility of our approach.